{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 加载数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore') # 忽略警告"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>班级</th>\n",
       "      <th>性别</th>\n",
       "      <th>男1000米跑</th>\n",
       "      <th>男1000米跑分数</th>\n",
       "      <th>男50米跑</th>\n",
       "      <th>男50米跑分数</th>\n",
       "      <th>男跳远</th>\n",
       "      <th>男跳远分数</th>\n",
       "      <th>男体前屈</th>\n",
       "      <th>男体前屈分数</th>\n",
       "      <th>男引体</th>\n",
       "      <th>男引体分数</th>\n",
       "      <th>男肺活量</th>\n",
       "      <th>男肺活量分数</th>\n",
       "      <th>身高</th>\n",
       "      <th>体重</th>\n",
       "      <th>BMI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4.13</td>\n",
       "      <td>72</td>\n",
       "      <td>8.88</td>\n",
       "      <td>66</td>\n",
       "      <td>195</td>\n",
       "      <td>60</td>\n",
       "      <td>12</td>\n",
       "      <td>74</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2785</td>\n",
       "      <td>62</td>\n",
       "      <td>170</td>\n",
       "      <td>72.599998</td>\n",
       "      <td>25.120001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4.16</td>\n",
       "      <td>70</td>\n",
       "      <td>7.70</td>\n",
       "      <td>78</td>\n",
       "      <td>225</td>\n",
       "      <td>74</td>\n",
       "      <td>11</td>\n",
       "      <td>74</td>\n",
       "      <td>7</td>\n",
       "      <td>60</td>\n",
       "      <td>3133</td>\n",
       "      <td>68</td>\n",
       "      <td>174</td>\n",
       "      <td>52.700001</td>\n",
       "      <td>17.410000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4.09</td>\n",
       "      <td>74</td>\n",
       "      <td>8.45</td>\n",
       "      <td>70</td>\n",
       "      <td>218</td>\n",
       "      <td>70</td>\n",
       "      <td>14</td>\n",
       "      <td>78</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3901</td>\n",
       "      <td>80</td>\n",
       "      <td>169</td>\n",
       "      <td>46.500000</td>\n",
       "      <td>16.280001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4.21</td>\n",
       "      <td>68</td>\n",
       "      <td>8.05</td>\n",
       "      <td>74</td>\n",
       "      <td>206</td>\n",
       "      <td>64</td>\n",
       "      <td>13</td>\n",
       "      <td>76</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4946</td>\n",
       "      <td>100</td>\n",
       "      <td>183</td>\n",
       "      <td>79.699997</td>\n",
       "      <td>23.799999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>3.44</td>\n",
       "      <td>85</td>\n",
       "      <td>7.52</td>\n",
       "      <td>78</td>\n",
       "      <td>210</td>\n",
       "      <td>66</td>\n",
       "      <td>13</td>\n",
       "      <td>76</td>\n",
       "      <td>9</td>\n",
       "      <td>68</td>\n",
       "      <td>3538</td>\n",
       "      <td>74</td>\n",
       "      <td>171</td>\n",
       "      <td>54.700001</td>\n",
       "      <td>18.709999</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   班级 性别  男1000米跑  男1000米跑分数  男50米跑  男50米跑分数  男跳远  男跳远分数  男体前屈  男体前屈分数  男引体  \\\n",
       "0   1  男     4.13         72   8.88       66  195     60    12      74    1   \n",
       "1   1  男     4.16         70   7.70       78  225     74    11      74    7   \n",
       "2   1  男     4.09         74   8.45       70  218     70    14      78    1   \n",
       "3   1  男     4.21         68   8.05       74  206     64    13      76    1   \n",
       "4   1  男     3.44         85   7.52       78  210     66    13      76    9   \n",
       "\n",
       "   男引体分数  男肺活量  男肺活量分数   身高         体重        BMI  \n",
       "0      0  2785      62  170  72.599998  25.120001  \n",
       "1     60  3133      68  174  52.700001  17.410000  \n",
       "2      0  3901      80  169  46.500000  16.280001  \n",
       "3      0  4946     100  183  79.699997  23.799999  \n",
       "4     68  3538      74  171  54.700001  18.709999  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nan_score = pd.read_excel('./体测分数_男生.xls')\n",
    "nan_score.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>班级</th>\n",
       "      <th>性别</th>\n",
       "      <th>女800米跑</th>\n",
       "      <th>女800米跑分数</th>\n",
       "      <th>女50米跑</th>\n",
       "      <th>女50米跑分数</th>\n",
       "      <th>女跳远</th>\n",
       "      <th>女跳远分数</th>\n",
       "      <th>女体前屈</th>\n",
       "      <th>女体前屈分数</th>\n",
       "      <th>女仰卧</th>\n",
       "      <th>女仰卧分数</th>\n",
       "      <th>女肺活量</th>\n",
       "      <th>女肺活量分数</th>\n",
       "      <th>身高</th>\n",
       "      <th>体重</th>\n",
       "      <th>BMI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>3.22</td>\n",
       "      <td>100</td>\n",
       "      <td>9.32</td>\n",
       "      <td>72</td>\n",
       "      <td>185</td>\n",
       "      <td>85</td>\n",
       "      <td>16</td>\n",
       "      <td>76</td>\n",
       "      <td>48</td>\n",
       "      <td>85</td>\n",
       "      <td>3775</td>\n",
       "      <td>100</td>\n",
       "      <td>163.0</td>\n",
       "      <td>51.299999</td>\n",
       "      <td>19.309999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>4.59</td>\n",
       "      <td>40</td>\n",
       "      <td>11.44</td>\n",
       "      <td>10</td>\n",
       "      <td>148</td>\n",
       "      <td>60</td>\n",
       "      <td>9</td>\n",
       "      <td>66</td>\n",
       "      <td>29</td>\n",
       "      <td>66</td>\n",
       "      <td>3683</td>\n",
       "      <td>100</td>\n",
       "      <td>163.0</td>\n",
       "      <td>66.599998</td>\n",
       "      <td>25.070000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>3.46</td>\n",
       "      <td>80</td>\n",
       "      <td>13.40</td>\n",
       "      <td>0</td>\n",
       "      <td>150</td>\n",
       "      <td>60</td>\n",
       "      <td>7</td>\n",
       "      <td>64</td>\n",
       "      <td>40</td>\n",
       "      <td>76</td>\n",
       "      <td>3331</td>\n",
       "      <td>100</td>\n",
       "      <td>157.0</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>24.340000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>3.39</td>\n",
       "      <td>85</td>\n",
       "      <td>9.52</td>\n",
       "      <td>70</td>\n",
       "      <td>172</td>\n",
       "      <td>76</td>\n",
       "      <td>21</td>\n",
       "      <td>90</td>\n",
       "      <td>46</td>\n",
       "      <td>85</td>\n",
       "      <td>3701</td>\n",
       "      <td>100</td>\n",
       "      <td>160.0</td>\n",
       "      <td>50.700001</td>\n",
       "      <td>19.799999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>3.43</td>\n",
       "      <td>80</td>\n",
       "      <td>9.79</td>\n",
       "      <td>68</td>\n",
       "      <td>145</td>\n",
       "      <td>50</td>\n",
       "      <td>8</td>\n",
       "      <td>64</td>\n",
       "      <td>34</td>\n",
       "      <td>70</td>\n",
       "      <td>3592</td>\n",
       "      <td>100</td>\n",
       "      <td>167.0</td>\n",
       "      <td>63.900002</td>\n",
       "      <td>22.910000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   班级 性别  女800米跑  女800米跑分数  女50米跑  女50米跑分数  女跳远  女跳远分数  女体前屈  女体前屈分数  女仰卧  \\\n",
       "0   1  女    3.22       100   9.32       72  185     85    16      76   48   \n",
       "1   1  女    4.59        40  11.44       10  148     60     9      66   29   \n",
       "2   1  女    3.46        80  13.40        0  150     60     7      64   40   \n",
       "3   1  女    3.39        85   9.52       70  172     76    21      90   46   \n",
       "4   1  女    3.43        80   9.79       68  145     50     8      64   34   \n",
       "\n",
       "   女仰卧分数  女肺活量  女肺活量分数     身高         体重        BMI  \n",
       "0     85  3775     100  163.0  51.299999  19.309999  \n",
       "1     66  3683     100  163.0  66.599998  25.070000  \n",
       "2     76  3331     100  157.0  60.000000  24.340000  \n",
       "3     85  3701     100  160.0  50.700001  19.799999  \n",
       "4     70  3592     100  167.0  63.900002  22.910000  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nv_score = pd.read_excel('./体测分数_女生.xls')\n",
    "nv_score.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 对男1000米跑、男引体进行等宽分箱操作，分成3份，并使用饼图绘制百分比"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib.font_manager import FontManager\n",
    "manager = FontManager()\n",
    "# 你电脑上 所有的字体，选择中文字体\n",
    "[ttf.name for ttf in manager.ttflist]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = pd.cut(nan_score['男1000米跑分数'],bins = 3,labels=['慢','中','快']).value_counts()\n",
    "percent = data/data.sum()\n",
    "plt.figure(figsize=(6,6))\n",
    "_ = plt.pie(percent,labels=percent.index,\n",
    "            autopct = '%0.2f%%',\n",
    "            textprops = {'family':'Kaiti SC',\n",
    "                         'fontsize':20})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = pd.cut(nan_score['男引体分数'],bins = 3,labels=['低','中','高']).value_counts()\n",
    "percent = data/data.sum()\n",
    "plt.figure(figsize=(6,6))\n",
    "_ = plt.pie(percent,labels=percent.index,\n",
    "            autopct = '%0.2f%%',\n",
    "            textprops = {'family':'Kaiti SC',\n",
    "                         'fontsize':20})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 对女800米跑、女跳远进行直方图绘制统计各分数段人数，分成4份"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(nv_score['女800米跑分数'],bins = 4,rwidth= 0.5)\n",
    "_ = plt.xticks([12.5,37.5,62.5,87.5])\n",
    "# 数据分成四份 0~25，25~50，50~75，75~100\n",
    "# 看图可知 75~ 100分的女生人数最多"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(nv_score['女跳远分数'],bins = 4,rwidth= 0.5)\n",
    "_ = plt.xticks([12.5,37.5,62.5,87.5])\n",
    "# 数据分成四份 0~25，25~50，50~75，75~100\n",
    "# 看图可知，跳远成绩 50~75分的女生人数最多"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 使用嵌套饼图对比男女生体重指数进行比例统计，分为正常、低体重、超重、肥胖"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "正常     0.759657\n",
       "超重     0.130901\n",
       "肥胖     0.081545\n",
       "低体重    0.027897\n",
       "Name: BMI, dtype: float64"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nan_BMI = pd.cut(nan_score['BMI'].round(1), # 保留一位小数\n",
    "                 bins = [0,16.4,23.2,26.3,100],\n",
    "                 labels=['低体重','正常','超重','肥胖']).value_counts()\n",
    "nan_BMI_percent = nan_BMI/nan_BMI.sum()\n",
    "nan_BMI_percent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "正常     0.759386\n",
       "超重     0.141638\n",
       "肥胖     0.081911\n",
       "低体重    0.017065\n",
       "Name: BMI, dtype: float64"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nv_BMI = pd.cut(nv_score['BMI'].round(1),#保留一位小数\n",
    "                 bins = [0,16.4,22.7,25.2,100],\n",
    "                 labels=['低体重','正常','超重','肥胖']).value_counts()\n",
    "nv_BMI_percent = nv_BMI/nv_BMI.sum()\n",
    "nv_BMI_percent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fc0b14b9fd0>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plt.figure(figsize=(9,9))\n",
    "plt.pie(nv_BMI_percent,radius=1,\n",
    "        autopct='%0.2f%%',\n",
    "        pctdistance=0.85,\n",
    "        labels = ['低体重','正常','超重','肥胖'],\n",
    "        wedgeprops={'linewidth':5,# 间隔的宽度\n",
    "                    'width':0.3, # 饼图的宽度\n",
    "                    'edgecolor':'white'},# 间隔的颜色\n",
    "        textprops={'family':'Kaiti SC','fontsize':18})\n",
    "\n",
    "_ = plt.pie(nan_BMI_percent,\n",
    "        radius=0.7,\n",
    "        autopct='%0.2f%%',\n",
    "        pctdistance=0.55,\n",
    "        wedgeprops={'linewidth':5,# 间隔的宽度\n",
    "                    'width':0.7, # 饼图的宽度\n",
    "                    'edgecolor':'white'})# 间隔的颜色\n",
    "\n",
    "plt.legend(['低体重','正常','超重','肥胖'],title = 'BMI',prop = 'Kaiti SC',)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6rc1"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
